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Record W6888854403 · doi:10.24406/publica-fhg-285325

Systematic presentation of the clean air policy individual OECD member states. Synopsis

2022· article· en· W6888854403 on OpenAlexaboutno aff

Bibliographic record

VenueFraunhofer-Publica (Fraunhofer-Gesellschaft) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsAir pollutionPresentation (obstetrics)Clean Air ActControl (management)Environmental policyPublic policyPreconditionEuropean union

Abstract

fetched live from OpenAlex

The knowledge about the special structures and basic ideas of the national policies on air pollution control constitutes the precondition for an international consensus on the policy on air pollution. Therefore all important fields have been collected for the 12 OECD countries Belgium, Federal Republic of Germany, France, Great Britain, Ireland, Italy, Japan, Canada, Austria, Sweden, Switzerland and USA. The aspects also include the strategies of the individual countries. Clear differences become evident when immission and emission standards are set up, and when principle of prevention resp. the polluter-pays-principle is applied. The strictest regulations are enforced in the Federal Republic of Germany, Switzerland, Sweden and Austria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.018
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.019

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.240
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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